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\title{A systemic approach to toxicogenomics}
\author{Franck Delaplace \and Cinzia Di Giusto \and Hanna Klaudel}
%\affiliation{Université d'Evry - Val d'Essonne, Laboratoire IBISC, Evry, France}

\begin{document}

\maketitle

\begin{abstract}
 \input{abstract.tex}
\end{abstract}
\todo{Notes: \\
- Since we are introducing a field that is relatively new, I would like to  have a long introduction, introducing the field and our contributions in detail.\\
- I am not sure we need to talk about CAD designers (see if they fit smoothly in the introduction), otherwise they could be mentioned in the conclusion where we sum up and discuss the results\\ 
- check punctuation}

\section{Introduction}
\input{intro}

\section{The model} \label{sec:reaction}
\input{reactionstamp}
\input{example}

% \section{Properties of Petri nets with timestamps}
% \input{properties}
% 
% 
% \section{Toxicology analysis}
% \todo{reachability analysys and bound proofs}
% %\input{toxic}
% 
% \section{Example: the interplay of Aspartame and Insulin}
% \todo{...}

\section{Discussion and concluding remarks}
\input{discussion}



% \section{Introduction}
% 
% We want to tackle problems of safety and security that arise when generating artificial bio-systems. We envisage to take as a starting point the language GUBS.
% 
% In an abstract manner, we can resume our problem in the following way. The wanted bio-system is specified through a “logical” specification: i.e. it is a formula in an hybrid temporal logic where causal relations are evidentiate. Through compilation ---that accounts in properly choosing bio components from a given database and then rewriting logic formulae--- we obtain a set of bio-components that by construction satisfies the following requirement: the “behavior” of the specification is included in the behavior of the so constructed bio-system. As a consequence we are guaranteed that the behavior of the specification is covered, but other, potentially harmful, reactions can also be triggered. This problem is worsen by two factors: the first one is connected to the fact  that databases are not standardized and bio-components can be described in sometimes even contrasting way  in different databases, the second one is linked to intrinsic biological aspects as not all the effects of a given component are 
%known, and some reactions can only be discovered through experiment.
% 
% At first we will assume that bio-components found in the chosen database are reliable: i.e. they are completely specified, all behaviors and reactions are known. At the state of the art, GUBS compilation only builds bio-components satisfying positive requirements: this way a first refinement could consist in handling also negative obligations (i.e. a specific reaction should not be observed/triggered).
% 
% Here we aim at building a framework that could support the development of Gubs program both  by providing a list of  negative premises that should be added as  input.
% Our approach consists of two steps: the first step is a translation of a given compiled program $Q$. 
% Following the foundation principles of GUBS, i.e. reversing casuses and effects we obtain a model that shows the minimal requirements for obtaining a certain effect. Once that this is done, we have obtained the input for the second step, that by following the cause effect direction should build the list of potential propducts of a given program $Q$.
% 
% \section{The translation}
% 
% \paragraph{First passage.}
% Given a GUBS program $P$, we compile it into a  program $Q$. We assume that this program is composed of the following rules only: 
% \begin{enumerate}
%  \item $ \norcause{k}{c_1 \dots c_n}{e}$ and
%  \item $ \percause{k}{c_1 \dots c_n}{e}$.
% \end{enumerate}
% 
% Starting from $Q$, we build a P/T net where each of the contests $k$, causes $c$ and the effects $e$ represents a particular place and where transitions are defined as in Figure \ref{fig:petri1}.
% For the first step, both normal and persistent dependencies are encoded in the same way.
% 
% \begin{figure}[t]
% \centering
% \def\svgwidth{0.3\textwidth}
% \input{petri1.pdf_tex}
% \caption{How normal and persistent dependencies are translated into P/T nets: 
% $ \norcause{k}{c_1 \dots c_n}{e}  $
% [$ \percause{k}{c_1 \dots c_n}{e}  $].
% }\label{fig:petri1}
% 
% \end{figure}
% 
% 
% \paragraph{Second passage.}


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